code: def test_gradient_descent():
      t1 = np.array([[-0.08], [1.02]])
      b1 = np.array([0.00])
      ada = Adaline(epochs=30, eta=0.01, minibatches=1, random_seed=1)
      ada.fit(X_std, y1)
      np.testing.assert_almost_equal(ada.w_, t1, decimal=2)
      np.testing.assert_almost_equal(ada.b_, b1, decimal=2)
      assert (y1 == ada.predict(X_std)).all()
  
file_path: mlxtend/mlxtend/classifier/tests/test_adaline.py
imports: import sys
  import numpy
  from sklearn.base import clone
  from mlxtend.classifier import Adaline
  from mlxtend.data import iris_data
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 4 for calling a global function with example usage: test_gradient_descent() without return types